Who Governs the Algorithm? Zimbabwe’s Missing AI Conversation

By Paul Nyausaru

Last week, this column argued that Zimbabwean organisations are largely stuck at AI awareness, unable to translate that awareness into structured action.
One reason for that paralysis deserves closer attention on its own: nobody inside most organisations has been given clear responsibility for governing how AI is actually used. Strategy documents mention AI. Board packs reference it.
But ask a typical Zimbabwean company who is personally accountable when an algorithm makes a bad or unfair decision, and the honest answer, in most cases, is: no one.
This is not a uniquely local failing. Globally, the pattern of AI adoption has followed a familiar and costly sequence: organisations deploy tools quickly because the technology is available and competitors are moving, discover governance gaps only after something goes wrong — a biased hiring algorithm that quietly filters out qualified candidates, a customer-facing system that makes decisions no one can fully explain, a data breach traceable to AI tools nobody vetted properly — and only then build the accountability structures that should have existed from the start. Retrofitting governance after a failure is always more expensive, in money and in trust, than building it beforehand.
Governance is not a document, it is a decision
There is a tendency to treat “AI governance” as a paperwork exercise: a policy drafted by IT or legal, filed away, rarely revisited. Real governance is not a document. It is a set of live decisions an organisation has made in advance: who has authority to approve a new AI tool before it touches customer data or employee records; what human oversight looks like when an algorithm recommends a hiring decision, a loan decision, or a disciplinary outcome; how the organisation responds when an AI system gets something wrong; and who is accountable, by name, when it does.
Zimbabwe is not starting from zero on this. Frameworks such as ISO 42001 already exist as a practical reference point for organisations wanting to build AI governance rather than invent it from scratch.
The Standards Association of Zimbabwe and the country’s data protection and cybersecurity authorities are actively engaging with what responsible AI adoption should look like in a Zimbabwean context. What is missing is not the raw material for good governance — it is the internal decision, inside individual organisations, to actually build it before it is legally or reputationally forced upon them.
Part of the difficulty is organisational, not technical. In many companies, AI sits awkwardly between departments that were never designed to own it jointly. IT owns the tools. Legal owns the risk language. HR owns the people affected by decisions AI increasingly influences.
Compliance owns the regulatory relationship. Each function assumes governance is somebody else’s job, and so, often, nobody’s job gets done.
The organisations getting this right are the ones building small, deliberately cross-functional AI governance structures — not a new department, but a standing conversation between the people who understand the technology, the people who understand the law, and the people who understand the human impact.
That last group matters more than it is usually given credit for.
As I argued last week, the organisations that will succeed with AI are not necessarily the most technically sophisticated ones, but the ones whose leaders have the emotional intelligence and honesty to say, when necessary, “we are moving too fast here” — and the authority within the organisation to actually slow down. Governance without that kind of leadership courage is just a document nobody enforces.
A conversation worth having together
None of this is an argument against AI adoption. It is an argument for adopting it deliberately rather than accidentally. Zimbabwean organisations have a genuine opportunity here: because the country’s professional bodies, regulators, and standards institutions are relatively well-connected, this is a conversation that can be had collaboratively, sector by sector, rather than each organisation quietly hoping to avoid becoming a cautionary tale.
That collaborative conversation is exactly what continues in Harare, at the TEG–TMCC AI Symposium 2026, on 27-28 October 2026 where regulators, standards bodies, and industry leaders sit down together to work through precisely these governance questions. Whether or not one attends, the underlying question will not go away on its own: someone, in every organisation using AI today, needs to be able to answer honestly who is actually governing it.
Paul Nyausaru is Founder and Executive President of Talent Exchange Group (TEG), an Organisation Development, Leadership, and HR consulting firm.
Nyausaru is the founder and executive president of Talent Exchange Group